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IET Cyber-Physical Systems
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Industrial multi‐energy and production management scheme in cyber‐physical environments: a case study in a battery manufacturing plant

Authors: Wei Pei; Xin Ma; Xin Ma; Wei Deng; Xinhe Chen; Hongjian Sun; Dan Li;

Industrial multi‐energy and production management scheme in cyber‐physical environments: a case study in a battery manufacturing plant

Abstract

Among the various electricity consumer sectors, the consumption level of the industrial sector is often considered as the largest portion of electricity consumption, highlighting the urgent need to implement demand response (DR) energy management. However, implementation of DR for the industrial sector requires a more sophisticated and different scheme compared to the residential and commercial sector. This study explores all the elastic segments of plant multi‐energy production, conversion, and consumption. We then construct a real‐time industrial facilities management problem as an optimal dispatch model to enclose these elastic segments and production constraints in cyber‐physical environments. Moreover, a model predictive‐based centralised dispatch scheme is proposed to address the uncertainties of real‐time price and renewable energy forecasting while considering the sequence of the production process. Numerical results demonstrate that the proposed scheme can enhance energy efficiency and economics of lithium battery manufacturing plant through responding to the real‐time price whilst ensuring the completion of production tasks.

Country
United Kingdom
Related Organizations
Keywords

690, production management, Computer engineering. Computer hardware, real-time industrial facilities management problem, cyber-physical environments, optimal dispatch model, sophisticated scheme, centralised dispatch scheme, TK7885-7895, case study, production constraints, production management scheme, commercial sector, pricing, consumption level, different scheme, energy management systems, industrial sector, electricity consumer sectors, production tasks, renewable energy sources, elastic segments, energy efficiency, plant multienergy production, residential sector, energy conservation, electricity consumption, 660, real-time price, power generation dispatch, largest portion, power consumption, lithium battery manufacturing plant, QA75.5-76.95, renewable energy forecasting, industrial multienergy, demand response energy management, Electronic computers. Computer science, production process

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    Top 10%
    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
10
Top 10%
Average
Average
Green
gold